k8s restful api 访问

restful api访问k8s集群，增删改查信息。

需要预先创建访问权限的配置。

官网api文档
https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.9/

下面罗列部分api

curl -u admin:admin “https://localhost:6443/api/v1” -k
curl -u admin:admin “https://localhost:6443/api/v1/pods” -k

curl -u admin:admin “https://localhost:6443/api/v1/namespaces/{namespace}/pods” -k
curl -u admin:admin “https://localhost:6443/api/v1/namespaces/default/pods” -k

获取节点信息

curl -u admin:admin "https://localhost:6443/api/v1/nodes/{nodename}" -k
curl -u admin:admin "https://localhost:6443/api/v1/nodes/tensorflow1" -k
 

  "status": {
    "capacity": {
      "cpu": "4",
      "memory": "7970316Ki",
      "pods": "110"
    },
    "allocatable": {
      "cpu": "4",
      "memory": "7867916Ki",
      "pods": "110"
    },

获取namespace信息

curl -u admin:admin "https://localhost:6443/api/v1/namespaces/{namespace}" -k
curl -u admin:admin "https://localhost:6443/api/v1/namespaces/default" -k

获得quota信息

curl -u admin:admin "https://localhost:6443/api/v1/namespaces/{namespace}/resourcequotas/" -k
curl -u admin:admin "https://localhost:6443/api/v1/namespaces/default/resourcequotas/" -k

实践

k8s_master_ip:192.168.1.138
username 不同用户不同
password 不同用户不同
namespace 不同用户不同

api地址
https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.10/
版本更新到v1.10以后 上面这个链接就找不到了 要把v1.9改成v1.10才能访问。

查看容器

curl -u {username}:{password} "https://{k8s_master_ip}:6443/api/v1/namespaces/{namespace}/pods/" -k
curl -u admin:admin "https://192.168.1.138:6443/api/v1/namespaces/default/pods/" -k  

看起来像是把所有的pod都拿出来了，包括活的和死的。
看了一下信息很多不过没有资源使用信息。

“phase”: “Running”
这个是正在运行的pod

“phase”: “Failed”
“reason”:“Evicted”
这种是删除了的，状态是failed 原因是被驱逐

增加continue参数取出正在运行的容器

curl -u {username}:{password} "https://{k8s_master_ip}:6443/api/v1/namespaces/{namespace}/pods?continue" -k
curl -u admin:admin "https://192.168.1.138:6443/api/v1/namespaces/default/pods?continue" -k

查看replicationcontroller

curl -u admin:admin "https://192.168.1.138:6443/api/v1/namespaces/user1/replicationcontrollers/" -k

查看service

curl -u admin:admin "https://192.168.1.138:6443/api/v1/namespaces/user1/services/" -k

查看资源总览resourcequotas

curl -u {username}:{password} “https://{k8s_master_ip}:6443/api/v1/namespaces/{namespace}/resourcequotas/” -k
[root@tensorflow1 info]# curl -u admin:admin “https://localhost:6443/api/v1/namespaces/default/resourcequotas/” -k

"status": {
  "hard": {
    "limits.cpu": "2",
    "limits.memory": "6Gi",
    "pods": "20",
    "requests.cpu": "1",
    "requests.memory": "1Gi"
  },
  "used": {
    "limits.cpu": "400m",
    "limits.memory": "1Gi",
    "pods": "2",
    "requests.cpu": "200m",
    "requests.memory": "512Mi"
  }
}

hard是限额 used是当前申请的限额
limits 和 requests 的区别是 limits是上限，不能突破，但不保证能给。 requests是下限，保证能给。 举例说明：一个容器 requests.memory 512Mi，limits.memory 1Gi。宿主机内存使用量高时，一定会留512Mi内存给这个容器，不一定能拿到1Gi内存。宿主机内存使用量低时，容器不能突破1Gi内存。
Gi 和 G 的区别是 Gi是1024进制，G是1000进制，M Mi也是同理。就像一个U盘8G但实际能使用的是7.45G(其实这里单位就是Gi)
pods是指容器，单位个
cpu单位 m指千分之一，200m即0.2个cpu。这是绝对值，不是相对值。比如0.1CPU不管是在单核或者多核机器上都是一样的，都严格等于0.1CPU core

实时数据

官方文档
https://kubernetes.io/docs/tasks/debug-application-cluster/core-metrics-pipeline/
https://github.com/kubernetes/metrics
https://github.com/kubernetes-incubator/metrics-server

下载 metrics-server 压缩包文件
下载 googlecontainer/metrics-server-amd64:v0.2.0
cd metrics-server-0.2.1/deploy
修改 metrics-server-deployment.yaml 文件 image 和 imagePullPolicy: IfNotPresent
kubectl create -f .

获取节点信息

curl -u {username}:{password} "https://{k8s_master_ip}:6443/apis/metrics.k8s.io/v1beta1/nodes" -k
curl -u admin:admin "https://192.168.1.138:6443/apis/metrics.k8s.io/v1beta1/nodes" -k
 
{
  "kind": "NodeMetricsList",
  "apiVersion": "metrics.k8s.io/v1beta1",
  "metadata": {
    "selfLink": "/apis/metrics.k8s.io/v1beta1/nodes"
  },
  "items": [
...
    {
      "metadata": {
        "name": "tensorflow1",
        "selfLink": "/apis/metrics.k8s.io/v1beta1/nodes/tensorflow1",
        "creationTimestamp": "2018-04-09T08:44:17Z"
      },
      "timestamp": "2018-04-09T08:44:00Z",
      "window": "1m0s",
      "usage": {
        "cpu": "265m",
        "memory": "3448228Ki"
      }
    }
...
  ]
}

获取pod信息

curl -u {username}:{password} "https://{k8s_master_ip}:6443/apis/metrics.k8s.io/v1beta1/namespaces/{namespace}/pods" -k
curl -u admin:admin "https://192.168.1.138:6443/apis/metrics.k8s.io/v1beta1/namespaces/default/pods" -k
 
{
  "kind": "PodMetricsList",
  "apiVersion": "metrics.k8s.io/v1beta1",
  "metadata": {
    "selfLink": "/apis/metrics.k8s.io/v1beta1/namespaces/default/pods"
  },
  "items": [
...
    {
      "metadata": {
        "name": "tensorflow-worker-rc-998wf",
        "namespace": "default",
        "selfLink": "/apis/metrics.k8s.io/v1beta1/namespaces/default/pods/tensorflow-worker-rc-998wf",
        "creationTimestamp": "2018-04-09T08:52:38Z"
      },
      "timestamp": "2018-04-09T08:52:00Z",
      "window": "1m0s",
      "containers": [
        {
          "name": "worker",
          "usage": {
            "cpu": "0",
            "memory": "39964Ki"
          }
        }
      ]
    }
...
  ]
}

获取namespace信息
没找到url，就把上面获取pod的使用量全加起来就是namespace的使用量了